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We use real replicas to investigate stability of thermodynamic homogeneity of the free energy of the Sherrington-Kirkpatrick (SK) model of spin glasses. Within the replica trick with the replica symmetric ansatz we show that the averaged…

Disordered Systems and Neural Networks · Physics 2009-11-10 V. Janis , L. Zdeborova

We consider a high-dimensional random constrained optimization problem in which a set of binary variables is subjected to a linear system of equations. The cost function is a simple linear cost, measuring the Hamming distance with respect…

Disordered Systems and Neural Networks · Physics 2022-11-23 Alfredo Braunstein , Louise Budzynski , Stefano Crotti , Federico Ricci-Tersenghi

We study the maximum-average submatrix problem, in which given an $N \times N$ matrix $J$ one needs to find the $k \times k$ submatrix with the largest average of entries. We study the problem for random matrices $J$ whose entries are…

Disordered Systems and Neural Networks · Physics 2024-01-24 Vittorio Erba , Florent Krzakala , Rodrigo Pérez , Lenka Zdeborová

In previous work, we have developed a simple method to study the behavior of the Sherrington-Kirkpatrick mean field spin glass model for high temperatures, or equivalently for high external fields. The basic idea was to couple two different…

Disordered Systems and Neural Networks · Physics 2007-05-23 Francesco Guerra

Let $A$ be an $n\times n$ random matrix whose entries are i.i.d. with mean $0$ and variance $1$. We present a deterministic polynomial time algorithm which, with probability at least $1-2\exp(-\Omega(\epsilon n))$ in the choice of $A$,…

Probability · Mathematics 2020-12-02 Vishesh Jain , Ashwin Sah , Mehtaab Sawhney

We discuss a general formalism that allows study of transitions over barriers in spin glasses with long-range interactions that contain large but finite number, $N$, of spins. We apply this formalism to the Sherrington-Kirkpatrick model…

Disordered Systems and Neural Networks · Physics 2009-10-30 L. B. Ioffe , D. Sherrington

Spin glass systems as lattices of disordered magnets with random interactions have important implications within the theory of magnetization and applications to a wide-range of hard combinatorial optimization problems. Nevertheless, despite…

Disordered Systems and Neural Networks · Physics 2025-10-28 Fredrik Hasselgren , Max O. Al-Hasso , Amy Searle , Joseph Tindall , Marko von der Leyen

We develop a mean-field theory for random quantum spin systems using the spin coherent state path integral representation. After the model is reduced to the mean field one-body Hamiltonian, the integral is analyzed with the aid of several…

Disordered Systems and Neural Networks · Physics 2007-11-20 Kazutaka Takahashi

We present the first iterative spectral algorithm to find near-optimal solutions for a random quadratic objective over the discrete hypercube, resolving a conjecture of Subag [Subag, Communications on Pure and Applied Mathematics, 74(5),…

Probability · Mathematics 2026-05-21 David Jekel , Juspreet Singh Sandhu , Jonathan Shi

We explore Langevin dynamics in the spherical Sherrington-Kirkpatrick model, delving into the asymptotic energy limit. Our approach involves integro-differential equations, incorporating the Crisanti-Horner-Sommers-Cugliandolo-Kurchan…

Probability · Mathematics 2024-01-09 Tingzhou Yu

Spin-glass systems are universal models for representing many-body phenomena in statistical physics and computer science. High quality solutions of NP-hard combinatorial optimization problems can be encoded into low energy states of…

Disordered Systems and Neural Networks · Physics 2020-01-14 Gavin S. Hartnett , Masoud Mohseni

We present a new dynamical proof of the Thouless-Anderson-Palmer (TAP) equations for the classical Sherrington-Kirkpatrick spin glass at sufficiently high temperature. In our derivation, the TAP equations are a simple consequence of the…

Mathematical Physics · Physics 2021-08-02 Arka Adhikari , Christian Brennecke , Per von Soosten , Horng-Tzer Yau

We explore the behavior of order parameter distribution of quantum Sherrington-Kirkpatrick model in the spin glass phase using Monte Carlo technique for the effective Suzuki-Trotter Hamil- tonian at finite temperatures and that at zero…

Statistical Mechanics · Physics 2018-03-01 Sudip Mukherjee , Atanu Rajak , Bikas K Chakrabarti

In 1977, Thouless, Anderson, and Palmer (TAP) derived a system of consistent equations in terms of the effective magnetization in order to study the free energy in the Sherrington-Kirkpatrick (SK) spin glass model. The solutions to their…

Probability · Mathematics 2024-03-26 Wei-Kuo Chen , Si Tang

Replica symmetry breaking postulates that near optima of spin glass Hamiltonians have an ultrametric structure. Namely, near optima can be associated to leaves of a tree, and the Euclidean distance between them corresponds to the distance…

Probability · Mathematics 2022-06-22 Antonio Auffinger , Andrea Montanari , Eliran Subag

In this paper we study the phase diagram of a Sherrington-Kirkpatrick (SK) model where the couplings are forced to thermalize at different time scales. Besides being a challenging generalization of the SK model, such settings may arise…

Mathematical Physics · Physics 2026-01-14 Francesco Camilli , Pierluigi Contucci , Emanuele Mingione , Daniele Tantari

We show that the only solutions of the TAP equations for the Sherrington-Kirkpatrick model of Ising spin glasses which can be found by iteration are those whose free energy lies on the border between replica symmetric and broken replica…

Disordered Systems and Neural Networks · Physics 2019-09-19 T. Aspelmeier , M. A. Moore

The Sherrington-Kirkpatrick spin-glass model is investigated by means of Monte Carlo simulations employing a combination of the multi-overlap algorithm with parallel tempering methods. We investigate the finite-size scaling behaviour of the…

Disordered Systems and Neural Networks · Physics 2007-05-23 Elmar Bittner , Wolfhard Janke

We study the problem of computationally efficient robust estimation of the covariance/scatter matrix of elliptical distributions -- that is, affine transformations of spherically symmetric distributions -- under the strong contamination…

Data Structures and Algorithms · Computer Science 2025-04-15 Gleb Novikov

Knapsack is one of the most fundamental problems in theoretical computer science. In the $(1 - \epsilon)$-approximation setting, although there is a fine-grained lower bound of $(n + 1 / \epsilon) ^ {2 - o(1)}$ based on the $(\min,…

Data Structures and Algorithms · Computer Science 2025-08-12 Xiao Mao